Role-Based Programme
RB1323

AI for Workforce Management

Advanced Forecasting, Scheduling & Real-Time Workforce Optimisation

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Duration
32 Hours
Level
Advanced
Delivery
Instructor-Led
Format
Capability Development

Programme Objectives

  • Develop advanced capability to apply AI across workforce forecasting, staffing, scheduling, intraday management, adherence, productivity, and performance monitoring.
  • Use AI-assisted analysis to identify demand patterns, coverage gaps, workload imbalances, staffing risks, absenteeism patterns, and productivity issues.
  • Apply AI to shift planning, roster optimisation, resource deployment, schedule adjustments, workforce communications, and operational reporting.
  • Use AI-assisted analytics to improve service coverage, workforce utilisation, schedule adherence, productivity, cost control, and operational responsiveness.
  • Build responsible AI-enabled Workforce Management workflows with strong fairness, privacy, governance, explainability, validation, and human oversight.

Tools covered

Generative AI AssistantsAI Search & ResearchWorkforce AnalyticsDemand Forecasting ConceptsStaffing Requirement AnalysisShift & Roster OptimisationSchedule Adherence AnalysisIntraday ManagementProductivity AnalyticsSkills-Based AllocationAbsence & Availability AnalysisWorkforce DashboardsWorkflow AutomationAI AgentsDecision-Support Tools

Who should attend

  • Workforce Management Managers
  • Workforce Management Analysts
  • Workforce Planning Professionals
  • Scheduling Managers
  • Roster Planning Professionals
  • Operations Managers
  • Contact Centre Workforce Managers
  • Service Operations Managers
  • Capacity Management Professionals
  • Resource Management Professionals
  • Workforce Performance Analysts
  • Operations Analysts
  • Shared Services Workforce Professionals
  • Workforce Optimisation Professionals
  • Leaders Responsible for Workforce Performance & Service Coverage

Prerequisites & Participant Readiness

  • Experience in workforce management, scheduling, operations, capacity planning, resource management, or service operations
  • Familiarity with workload forecasts, staffing requirements, rosters, adherence, productivity, and workforce KPIs
  • Basic awareness of Generative AI and common business applications
  • Comfort working with workforce, schedule, demand, and performance data
  • No programming knowledge required

TOC Modules

Concepts
  • Understanding Generative AI, reasoning models, workforce analytics, automation, and AI agents
  • Exploring AI applications across forecasting, scheduling, adherence, productivity, and intraday operations
  • Distinguishing AI-assisted workforce decisions from autonomous employee-management decisions
  • Understanding hallucinations, employee-data sensitivity, bias, and human accountability
Practical activities
  • Mapping AI opportunities across the Workforce Management lifecycle
  • Identifying activities suitable for augmentation, automation, or continued human ownership
  • Creating an AI opportunity map for Workforce Management teams

Scenarios

Daily Service-Level Failure to Intraday Workforce Recovery Plan

Demand Spike → Staffing Gap → Schedule Adherence → Skill Availability → Queue Pressure → Resource Redeployment → Schedule Adjustments → Service Recovery

Participants use AI to analyse a real-time workforce shortfall, identify the combination of demand, staffing, skills, and adherence issues, and create a practical intraday recovery plan.

High Overtime & Poor Schedule Fit to Workforce Optimisation Model

Demand Patterns → Staffing Requirements → Roster Design → Shrinkage → Overtime → Occupancy → Cost & Service Impact → Optimised Schedule

Participants use AI to diagnose persistent overtime and poor roster alignment, compare alternative shift and staffing models, and create a more balanced workforce plan that improves service coverage and cost efficiency.

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